Mailman 3 December 2014 - pypy-dev

use as benchmark pypy vs python if you please
by Dima Tisnek 13 Sep '15

13 Sep '15

Attached is n-queens solver (pardon my naive algorithm), it runs: python 2.7.6: 17s pypy 2.4.0 alpha: 23s same nojit: 32s I've tried similar-looking algorithm for another problem before, and has similar results -- somehow pypy was slower. feel free to investigate / tweak or even use on speed.pypy.org

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Poor performance for Krakatau
by Robert Grosse 10 Aug '15

10 Aug '15

In some cases, Pypy performs worse than CPython when running Krakatau, and it has gotten a lot worse from 2.3 to 2.5 My benchmark is https://github.com/Storyyeller/Krakatau/tree/pypy_benchmark (for future reference, commit d889c7f44723e6d66a3630681f0385f173317dc9) You can run it with pypy Krakatau\benchmark.py -path <path to Java rt.jar> I get the following timings CPython: 17.43s Pypy 2.3: 38.48s (build pypy-c-jit-71056-c8e3b8cbc843-win32) Pypy 2.4: 39.92s (build pypy-c-jit-72200-375133966c12-win32) Pypy 2.5: 49.94s (build pypy-c-jit-74404-9fd586fe0fe5-win32) Not only was it slower than CPython to begin with, but it got much worse recently.

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Re: [pypy-dev] Ask Pypy within virtualenv of Windows 7/8 for Help ---- bitpeach from china
by Matti Picus 07 Jan '15

07 Jan '15

The latest released virtualenv is version 1.11.6 which does not support pypy 2.4.0 and earlier on windows. A fix was merged into virtualenv after this version (released 17 May 2014) so any newer release will be fixed. In the mean time you can: 1. run "virtualenv -p path\to\pypy.exe new_path" and it will fail 2. copy by hand the directories lib_pypy and lib-python from path\to to new_path 3. rerun virtualenv, it should complete cleanly after installing setuptools and pip Matti > Dear Ms./Mr. Director / Dear Pypy Team: > I'm a e-pal named bitpeach. I'm so interested in your work and > admire the Pypy. > Therefore, I try to install Pypy and pratice with Pypy during my > working and studying. But I got a problem, what is worrying me is that > there is few versions of Pypy running on the Windows. So the problem > comes as follows: > (1)I want to instal Pypy but do not confuse the the 3rd packages > or libraries with Python2.7 already in my operate system Windows 7/8 > (32bit). Then I choose to follow the tutorial settings to install > VirtualEnv just like "Installing using virtualenv". > ... bitpeach > 2014-12-13 Sat. > Email From China > > > _______________________________________________ > pypy-dev mailing list > pypy-dev(a)python.org > https://mail.python.org/mailman/listinfo/pypy-dev >

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stdlib-2.7.9!
by Alex Gaynor 03 Jan '15

03 Jan '15

Hey all, Earlier today I created the 2.7.9 branch, with the copy of the 2.7.9 stdlib. http://buildbot.pypy.org/summary?branch=stdlib-2.7.9 is the branch summary. It's no surprise, the biggest work to be done is for the ssl module, 2.7.9 contains a complete backport of 3.4's ssl module. We have up through 3.2s version of the ssl module implemented on the py3k branch. I'd like some feedback from folks on how you think we should best handle finishing the 2.7.9 work. Should I copy the work from py3k, finish anything missing, and then when we get to python 3.4 on the py3k branch the work is just "already done"? Something else? Feedback please! Alex

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How do I get better jit_libffi traces?
by Timothy Baldridge 31 Dec '14

31 Dec '14

I'm trying to optimize the FFI functionality in Pixie, and I'm not sure how to proceed. From what I understand, the JIT generator is able to optimize away calls to jit_libffi and simply replace them with bare calls to the c functions. However, not matter how I hint or mark things as immutable, I seem to always have a call to "jit_ffi_call_int". What exactly triggers the JIT to remove that call? The part of the trace involved in the jit call looks like this: https://gist.github.com/halgari/31b188e8e4757ccb3218 Any ideas? Thanks, Timothy

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--shared on osx
by Wouter van Heijst 31 Dec '14

31 Dec '14

Hei all, at the moment --shared on OSX is broken, merging the following PR: https://bitbucket.org/pypy/pypy/pull-request/293/shared-support-on-osx/ should take care of it. Is there anything I can do to move the pull request forward? Cheers, Wouter

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ufuncapi branch
by Matti Picus 29 Dec '14

29 Dec '14

I have been plugging away at getting linalg support working via the ufunc capi in cpyext. It turns out that the branch can actually run much of linalg, and does not crash pypy. The ufunc api is a very convoluted, it uses a function-selection mechanism based on dtypes, and function interface specification via signatures. I am sure I have not covered all the corners with the tests that exist in micronumpy, and the numpy tests seem very minimal as well, but it seems to work as advertised. Currently numpy's linalg uses the cpyext interface, my next step should be to use cffi instead via the extended frompyfunc() interface that supports most of the ufunc capi arguments, this work will happen in the cffi-linalg branch of pypy/numpy. I would like to merge the ufuncapi branch of pypy to default, that would make work on the pypy/numpy repo easier. Are there objections and/or does anyone know of a wider suite of tests of ufuncs? Matti Note that we now have a solution for getting non-ui matplotlib plots: - translate the pypy ufuncapi branch - set it up in a virtualenv - install the cffi-linalg branch of pypy/numpy - install github.com/mattip/matplotlib This is sufficient to run the python-benchmarks repo from https://github.com/numfocus/python-benchmarks

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Some work on virtualenv
by Armin Rigo 26 Dec '14

26 Dec '14

Hi all, Some work started on the virtualenv refactoring that some people here might be interested to hear about: https://github.com/pypa/virtualenv/pull/691 A bientôt, Armin.

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recent commit to pypy/numpy build-shared-object
by Matti Picus 25 Dec '14

25 Dec '14

I would like to hear what you think about the build-shared-object branch on pypy/numpy The goal is to buld a pure shared object for cffi rather than a traditional python module I used link_shared_lib() from the distutils ccompiler|, |||but had to hack a bit to get it to play nicely with the numpy build system. Any comments would be appreciated. Matti

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Getting rid of "prebuilt instance X has no attribute Y" warnings
by Timothy Baldridge 19 Dec '14

19 Dec '14

I'm getting a ton of these sort of warnings. They seem to go away when I either a) type hint the object via assert (gross) or b) access the attribute via a getter method. Is there a better way? Would there be a problem with somehow just turning this warning off? Thanks, Timothy

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